关键词: 惯性法则, 基因调控网络, 粒子群优化算法, DNA修复网络, 时序基因表达数据

Abstract: By combining with genetic regulatory networks’ nonlinear characteristic，an improved differential dynamical model based on the inertia principle is presented in this paper.The derivations demonstrate that it can work like the recurrent neural network.The experimental results for a time series gene expression data of DNA Repair networks indicate that with the help of the particle-swarm-optimization based training procedure for the parameter adjustment，the proposed model is effective.

Key words: inertia principle, gene regulatory networks, particle swarm optimization, DNA repair networks, time series gene expression data